Evaluation of Multi-Functional Variable Refrigerant Flow System With Thermal Energy Storage and Photovoltaic-Based Distributed System for Net-Zero Energy Home Design

The building sector represents one of the largest energy consumers in the United States, accounting for approximately 40% of total energy consumption [1]. Energy consumption in buildings is anticipated to continue rising, as newly constructed modern buildings are occupied more quickly than older ones are retired. These new buildings often consume more energy per unit area, utilizing advanced electric appliances and heating and cooling technologies to satisfy occupants’ desires for convenience and comfort. Residential buildings comprise the largest portion of primary energy consumption [2].

Net-zero energy homes (NZEHs) present a viable solution for reducing energy consumption in residential buildings [3]. The net-zero energy concept for building applications combines renewable energy systems with energy-efficient construction and appliances, resulting in net-zero energy consumption [4]. The benefits of NZEHs encompass improved comfort, economic satisfaction, and energy and environmental sustainability. Berry et al. [5] conducted a study to explore the opinions of individuals residing near NZEHs. They interviewed 25 households and collected energy data from over 50 near NZEHs. All households expressed satisfaction with their low energy bills and noted that the energy costs from their near-net energy home were lower than those in their previous residences.

Because of the advantages NZEHs offer, numerous codes and regulations have been established to promote energy efficiency in homes. For example, Delaware’s Title 16, under Chapter 76 and Section 7602, Code for Energy Conservation, sets the programs to promote the building construction market to adopt and construct net-zero energy homes. They have set a goal for all new residential buildings in Delaware to achieve net-zero performance in Delaware by 2025 [6]. Similarly, California is also at the forefront of the NZEH legislation. The California Long-term Energy Efficiency Strategic Plan’s goal requires all new residential buildings be constructed to NZEH standards by 2020 [7]. With these objectives in place, many NZEHs have been built, and related projects actively support the NZEH movement.

It is important to discuss the designs of NZEHs, as they encompass crucial components that can substantially influence their efficiency and benefits. One such component is the heating, ventilating, and air-conditioning (HVAC) systems, which can account for a considerable portion of a building’s total energy consumption, ranging from 20% to 40% [8]. The US Energy Information Administration (EIA) predicts that air-conditioning energy use in buildings will grow at a faster rate than other uses, such as electronics, water heating, cooking, and more [9]. Consequently, HVAC systems represent a significant component to address in NZEH design. Wu et al. [10] compared three different HVAC options (ventilation, dehumidification, and heat pump) for a NZEH and found that careful selection of an HVAC system can optimize energy reduction.

Numerous HVAC systems are available; however, this study concentrates on the variable refrigerant flow (VRF) system due to its energy efficiency and heat recovery (HR) capabilities. VRF systems are considered as advanced HVAC technology that delivers heating and cooling by circulating refrigerant between an outdoor unit and multiple indoor units. These systems modulate the refrigerant flow in response to the cooling or heating demand of each individual indoor unit effectively, ensuring optimal temperature control, maintaining desired indoor thermal comfort, and reducing energy consumption. Gilani et al. [11] conducted a study analyzing the energy performance of a residential building in Cyprus that integrated a VRF system along with photovoltaic (PV) arrays. They found that installing the PV system reduced about 14 tons of CO₂ each year, and the PV arrays satisfied 126–166% of the VRF’s annual energy demands. Li et al. [12] developed a cooling system that uses solar and geothermal energy with underground soil space as cold energy storage for a nearly zero-carbon cooling target in a residential building. Their simulated results demonstrated that the proposed system could provide naturally free space cooling in a single house without using heat pumps and air conditioners. Lee et al. [13] compared a VRF system with a rooftop unit (RTU) variable-air-volume (VAV) system based on results from field tests and energy simulations. Their results showed that the VRF system reduced HVAC energy usage by 17% and 74% during cooling and heating operations, respectively. With HR technologies of VRF systems, the savings potential of HVAC energy can be maximized while meeting thermal comfort inside buildings [14]. Li and Wu [15] assessed the savings potential of HVAC energy with a VRF-HR system through a simulation-based analysis. The study concluded that the VRF-HR system had about 16% energy savings compared to a typical VRF system. In addition, Kim et al. [16] assessed the savings potential of a VRF system by comparing it with the RTU-VAV system in a simulated-based analysis under US climate conditions. Their simulated results observed that the VRF system could save up to 40% and 33% for HVAC site and source energy use, respectively, based on the US climate. Kim et al. [17] also proposed a HR-enabled VRF system with hydraulic heat exchangers for domestic hot water (DHW) and evaluated its energy savings potential based on a case study of a commercial building. Their investigation revealed that their proposed system could save about 22–24% of total building energy savings annually in US climate conditions compared to a conventional HVAC system.

The effectiveness of NZEH designs may vary depending on the climate and weather conditions of the location. For example, heating-dominant climates (such as Climate Zones 6 and 7) in the US may require superinsulated components to reduce the heating load in a NZEH, while hot and milder climates may benefit from more open houses with renewable energy systems [18]. Consequently, many studies on building energy efficiency have been conducted across various climates. Kim et al. [19] found that life cycle cost (LCC) values for net-zero energy buildings (NZEBs) differ across different US climates, with some hot and mild climate areas having lower LCC values than cold climate areas. Research on HVAC system performance in net-zero energy buildings has also been conducted, as HVAC systems play an integral role in NZEH designs. One key factor that influences HVAC demand in residential applications is the climate where the building is located. Jazaeri et al. [20] explored the influence of building envelopes, various climates, and occupancy on residential HVAC demand. They found that the highest energy reductions occur in different climate locations with high diurnal temperature variation. They also found that the varied Australian climates, ranging from tropical to cold temperate, greatly impact HVAC demand. Kharseh et al. [21] investigated how climate warming conditions can affect heating and cooling demands and HVAC energy use variations in residential buildings. They concluded that the heating load reduction could vary from 10% in a cold climate to 55% in a hot climate, while the increase in cooling load ranges from 10% in a hot climate to 34% in mild weather. The changes in annual energy use for HVAC systems could differ from −7.4% in a cold climate to 12.7% in a hot climate.

Climate conditions also significantly affect the potential of on-site distributed power generation. Qandil et al. [22] presented a case study to optimize renewable energy systems for a typical residential building in US states. The study showed that the best configuration for solar and wind energy systems combined with different energy storage systems was a PV-based integrated system with a battery. They also highlighted that the daily solar irradiation and energy prices substantially affect the cost-effectiveness and nearly NZEBs achievement. Kim et al. [23] evaluated the potential effects of inattentive NZEB implementations on electricity demand profiles on the US electrical grid. Their simulated results showed that annual electricity consumption (e.g., cooling and heating) and distributed PV power generation could significantly vary depending on the climate conditions. Houchati et al. [24] presented a day-ahead solar energy forecasting method to optimize energy balances between the utilization of available solar energy resources and energy demands. They also investigated the control system to manage the demand side in different climate regions, leading to smart building energy management and zero energy building goals. Becker et al. [25] presented geothermal system integration for zero community-scale adoption as electric and thermal resources in cold climates. In their conclusion, they mentioned that the proposed geothermal system could be cost-competitive with rooftop PV systems, resulting in significant savings in site energy import and export, depending on geothermal resource potential in climate. Numerous existing studies demonstrate that achieving zero energy performance relies on several factors, including building types, implemented energy-efficient technologies, and climatic context. Effectively attaining NZEH performance necessitates the selection of energy-efficient HVAC systems and renewables to enhance home energy balances, ultimately reaching NZEH performance goals. Although many studies have presented advanced HVAC applications to effectively achieve zero energy performance in buildings with renewables (e.g., solar PV systems), HVAC-related heat recovery technologies have not been sufficiently explored for NZEH performance, particularly when combined with a hot water loop and thermal storage configurations.

This study aims to evaluate the effectiveness of the proposed NZEH design in various US climate zones by incorporating a multi-functional VRF system combined with a thermal energy storage system. The thermal storage system in the proposed design is connected to a domestic hot water loop to reduce hot water energy use. The proposed NZEH also considers a PV-based distributed system to generate on-site electricity, which is used to offset the remaining energy end-use for NZEH design. The baseline model, used to assess the proposed design, is validated using the net-zero energy residential test facility (NZERTF) from the National Institute of Standards and Technology (NIST). To evaluate the savings impact of the proposed NZEH design with the VRF system, annual energy end-use and on-site power generation reductions are compared before and after implementing the VRF system in the baseline design. The methodology section provides more detailed information on the analysis.

To enable appropriate NZEH design, it is essential to consider energy-efficient passive and active technologies. A simulation-based study has been conducted to assess the energy savings potential of the proposed NZEH design. The building and system information of a NZERTF developed by the NIST [26] is used to create the target NZEH simulation model. This study employs the NZERTF as a benchmark design primarily because NIST’s NZERTF was designed and constructed to demonstrate typical NZEH performance with conventional architecture, amenities, and home size comparable to other similar conditions [27,28]. The methodology section in this section outlines how the NZEH model was developed using eQUEST and incorporates an energy-efficient HVAC system as an alternative to propose a more energy-efficient NZEH design.

The simulated NZEH model is designed based on NIST’s NZERTF. The NZERTF is a net-zero residential home located in Maryland, and it provides field data that researchers use to validate and improve energy models. The house has various features and capabilities, such as a photovoltaic system with a reconfigurable array that lets researchers select four power outputs between 2.6 and 10.2 kW. Its capabilities also include evaluating models that can predict the amount of energy produced annually from solar energy systems, evaluating design strategies to deliver quality indoor environments that meet energy efficiency goals, and much more [27].

The NZERTF is a two-story house with a living space area of 252 m² and a conditioned basement area of 135 m² with a true south-facing direction. A 3D model is created using as-built architectural plans. Each floor of this building consists of different functional spaces to meet its NZEH demonstration phase goal. The first floor has a family room, an office space, and a kitchen and dining area. The second floor includes a master, two children’s bedrooms, a bathroom, and a hallway. Figures 1(a) and 1(b) present the perspective view of the single-family NZERTF (Gaithersburg, MD, USA) that we adopt to benchmark a NZEH model and eQUEST model that we developed based on NIST’s information, respectively.

Major components that affect the thermal behaviors in a building include the building envelope and internal heat gains. NZEH performance features a wide array of energy-efficient technologies and equipment. Table 1 summarizes the main geometry and internal heat gains used for the NZEH simulation model. More detailed modeling data and information can be found in Refs. [26–28]. In the measurement process, the house was simulated to be unoccupied. Using computer-controlled appliances, plug loads, lighting, water usage, and devices, a family of four’s energy consumption and daily routines were simulated and replicated [27]. In building energy simulation, modeling the impact of internal heat gains (e.g., occupancy, lighting, and internal equipment) requires internal heat gain intensity and operation schedules. All internal heat gain intensity values and schedules are directly obtained from NIST’s studies [27,28]. The NIST schedules were implemented based on the Building America program. The NIST building has a high-performance thermal envelope, including higher insulation layers, double-paned windows, and airtight construction, as presented in Table 1, compared to the 2012 International Energy Conservation Code (IECC) standard.

For the baseline HVAC system, this study adopts the multispeed air-to-air heat pump (ASHP) to provide the primary heating and cooling, which is one of the installed HVAC systems in the NZERTF.

The specified capacity of the ASHP obtained from NIST’s studies [26–28] is first used for the validation process in the eQUEST simulation modeling. After proper validation, the cooling and heating capacities are determined based on design day conditions. For each conditioned zone, cooling and heating design supply air temperatures are assumed as values shown in Table 2. The thermostat setpoint temperatures are assumed to be 23.8 °C and 21.1 °C for cooling and heating during occupied hours. Multispeed cooling and heating coils are implemented in the eQUEST model (i.e., low speed and high speed). Each coil has two coefficient of performance (COP) values corresponding to the multispeed operations. Table 2 presents HVAC and domestic hot water system specifications used to implement the NZEH model in this study. Detailed HVAC design and operational information can be found in Refs. [26–28].

Hot water supply in the NZERTF can be provided by either the combined DHW system with a solar thermal system and a heat pump water heater or with only a heat pump water heater. In this study, the DHW system with a heat pump water heater system is modeled and used as a baseline system. The exit water setpoint temperature of the DHW system is assumed to be 50 °C.

HR technologies of VRF systems can be considered to maximize energy savings for both commercial and residential buildings [17,29]. This study proposes adopting a HR-enabled VRF system with a hydraulic heat exchanger as an alternative NZEH design for the NIST’s NZERTF. With the proposed system, the energy savings potential of HVAC and DHW systems can be maximized by minimizing waste heat through a VRF outdoor unit. Unlike large commercial buildings with simultaneous heating and cooling energy demands, single-family residential buildings can typically experience the same thermal load patterns for all thermal zones within a building. With such limitations, achieving high energy savings potential can be difficult unless the thermal load patterns dramatically differ among conditioned spaces in residential buildings. However, the heat recovery potential can be increased by integrating a domestic hot water loop with the VRF system.

This study introduces a multi-functional variable refrigerant flow system with a hydraulic heat recovery to enhance energy savings in existing HVAC technology by incorporating a DHW loop. Figure 2 depicts the schematic of the proposed multi-functional variable refrigerant flow system with hydraulic heat recovery (MFVRF-H2R) system, showcasing each component and piping connection used in the simulated model. This schematic presents a configuration that combines one outdoor unit and four indoor units, including one water heat exchanger. The MFVRF-H2R system is designed for the three-pipe VRF heat recovery system, which is a prevalent configuration in the current VRF heat recovery systems marketplace. The three-pipe VRF heat recovery system features dedicated refrigerant pipes for suction gas, liquid, and discharge gas. A heat recovery unit and four-way valves are employed to enable separate refrigerant piping connections for different operational modes.

With respect to the H2R connection side, the H2R unit is incorporated into the baseline DHW system. Each component of this proposed system features specific piping connections to facilitate refrigerant flow in various directions through the HR unit. This figure illustrates that the H2R unit and individual indoor units are connected to the HR unit box, which is directly coupled to a VRF outdoor unit. The H2R unit is compatible with three-phase VRF systems and heat recovery outdoor units, enabling the preheating of DHW stored in an indirect storage tank, as depicted in Fig. 2. This proposed system employs the R134A-refrigerant throughout the piping connection to a water heat exchanger to produce heated water based on the heat extracted from the indoor units’ refrigerant operating in cooling mode.

Figure 3 depicts the proposed system’s flowchart of calculation steps and operating conditions. The calculation is conducted based on a post-process calculation method. Depending on the indoor thermal requirements, the operation mode of the proposed system can be determined to maximize the heat recovery savings potential of space heating or DHW and minimize VRF outdoor load. Hourly indoor thermal loads used for post-process calculations are derived from the eQUEST whole-building energy simulation. To estimate the cooling and heating demands of the MFVRF-H2R system, the curve-based model of the VRF system in eQUEST is employed. eQUEST utilizes the zone air balance method to determine cooling and heating requirements while maintaining each conditioned zone’s setpoint temperature. The cooling and/or heating demands determined for each VRF indoor unit can be utilized to calculate the total cooling/heating demands on the VRF outdoor unit, considering the piping correction factor and various other conditions, such as rated capacity, combined ratio, and actual operating conditions. This study employs eQUEST’s VRF model to simulate required cooling and heating demands without modification.

The calculation flowchart is composed of several key parts. The first part determines the operation mode of VRF heating or cooling based on cooling/heating requirements from individual VRF indoor units. There are five operation modes for the MFVRF-H2R design: (1) cooling-only mode, (2) cooling-dominant mode, (3) cooling and heating balanced mode, (4) heating-dominant mode, and finally (5) heating-only mode. Then, the available heat recovery potential of the proposed MFVRF-H2R system is determined. The required hot water storage capacity can also be determined in this process. The recovered heat is then calculated to determine DHW and VRF outdoor unit load reductions. Finally, the electrical energy end-use of the MFVRF-H2R and DHW system is computed and compared to the existing system to evaluate its energy savings potential.

To enable NZEH performance for a residential building, this study considers a grid-tied PV generation system assuming that a net-metering connection between the simulated home and the electrical grid is available. The PV calculation model in eQUEST is used to predict on-site PV generation. This model uses equation-based calculation for an empirical equivalent circuit model to determine the current-voltage features of a single module and its array configuration [30].

Table 3 summarizes the characteristics of PV model performance. The size of PV capacity is determined based on NIST’s study [26]. Featuring a nominal efficiency of 20.5%, the fixed PV modules are mounted on the south-facing roof surface with a tilt of 18.4 deg, as illustrated in Fig. 4. Although the optimal tilt angle for PV installation may vary according to geographical locations, this study maintains the same tilt angle across all climate locations. This approach is primarily due to the assumption that PV modules are fixed on the south-facing roof exterior surface. The total installed PV capacity for the baseline is 10.2 kW p, covering an area of 50 m². The capacity and area of a single PV module are 364 Wp and 1.8 m², respectively, with 28 PV modules employed in the baseline design.

Figure 4 presents the schematic PV system with the net-metering operation for the NZEH model. This study assumes that surplus power from the on-site PV generators can be fed into the electrical grid. Consequently, all excess electricity produced by the on-site PV system, after meeting the home’s requirements, can be fed back into the electrical grid through the met-metering agreement. It is important to note that the nominal efficiency throughout the transformer between the building side and the electrical grid side is set to 100%, without considering transfer losses.

The validation process is conducted to ensure that the author’s simulation model (i.e., baseline) can predict both building energy and on-site power generation in an acceptable manner before implementing the proposed system. This study considers the whole-building calibrated simulation approach in American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Guideline 14-2014 [31]. This guideline states that the acceptable tolerances are 15% coefficient of variation of root mean square error (CV-RMSE) and 5% normalized mean bias error when using monthly data.

Figure 5 shows the monthly comparison of whole-building energy end-use and on-site power generation for the author’s modeling output versus NIST’s measured [26] and simulated data [27]. The whole-building energy end-use is based on all the electrical energy consumption, including lights, non-HVAC interior equipment (e.g., home appliances and any miscellaneous electrical loads), heat pump hot water system, and HVAC energy use in the building.

As seen in this figure, the author’s simulation model shows good agreement in most months after April, with 14.4% and 15.7% CV (RMSE) for NIST’s measured and simulated results, respectively. Because the measured data obtained from Ref. [26] have relatively high energy usage during the first three months compared to the building design-based simulation models, those three months’ data are not considered in this statistical validation. The NIST’s building design-based modeling [27] indicates the created whole-building energy simulation to replicate the NZERTF design and estimate its energy performance before the actual demonstration phase begins. In Fig. 5, several unmatched months exist (e.g., April and August). It could be expected that major differences between author’s modeling and NIST’s one could be caused by various sources of uncertainty in building energy simulation, including some simplifications for the inputs that affect indoor thermal behaviors or limited information and assumption for the modeling features. For example, this study assumes using a heat pump water heater with no solar thermal system, but NIST’s analysis included solar thermal energy. In addition, building geometry (e.g., roof shapes) and some other factors, such as operation schedules, might not be fully mimicked in the modeling process.

Figure 5 also shows the monthly comparison of on-site PV production. The monthly compared results present that the PV model in eQUEST can predict the on-site PV power generation with a good agreement between the author’s simulated model and NIST’s data, including about 15.0% and 8.4% of CV (RMSE) values for NIST’s simulated model and measured data, respectively.

The validated model is modified to setup baseline models that follow the requirements of ASHRAE Standard 90.2 [32] under various climate conditions. The key contribution of this 90.2 standard is delivering an accurate, flexible, performance-based tool to enable user creativity in residential building energy performance [26]. In this study, a key modification to the validated model is the COP values of the ASHP system under different climate locations. Based on the standard, the modified baseline model adopts the seasonal coefficient of performance value of 3.81 instead of the COP values summarized in Table 2.

Figure 6 compares the whole-building energy end-use on a monthly basis for each comparative case. The author’s modified baseline refers to the developed baseline model after the COP modification. As expected, the energy use patterns of the modified baseline tend to decrease during summer months and increase during winter months primarily due to a relatively higher cooling COP value during the cooling season and lower heating COP value compared to the original system. The modified baseline model is used to evaluate the savings potential of the proposed NZEH design with a multi-functional VRF system under US climate conditions.

The energy savings potential and required PV capacity of the proposed NZEH with a multi-functional VRF system under various US climate conditions are evaluated in this section. The simulated NZEH models with each HVAC system are placed in seven different climate zones. Table 4 presents seven representative climate zones and their weather conditions, constructed by the IECC and identified in ASHRAE Standard 90.1-2013 [33]. Each climate zone shown in this table represents one representative location, including 1A, 2A, 3A, 3B, 4A, 4C, and 5A for Miami, FL, Houston, TX, Atlanta, GA, Los Angeles, CA, Baltimore, MD, Seattle, WA, and Chicago, IL, respectively. Table 4 also shows the maximum dry-bulb temperatures of heating and cooling design days for each climate. Based on the design days conditions, the system capacity of the corresponding VRF indoor and outdoor units can be auto-sized and used for an annual simulation process. Note that this study did not consider extreme cold weather climates, such as climate zones 6A and 7, because the dominant heating type in those areas is the natural gas furnace for energy-efficient operation, and this study only considered heat pump space heating.

This section presents compared results between the baseline and the proposed models to evaluate savings potential when the NZEH considers MFVRF-H2R for the HVAC alternative under various US climate conditions. In the first part of this section, the NZEH performance is investigated for the need of PV capacities to reach NZEH balances over a yearly cycle in representative climate locations. Under the NZEH performance, the savings potential of building energy end-use and PV installation capacity is then discussed when the MFVRF-H2R is applied to the NZEH baseline model.

Figure 7 depicts the scatter plots of each NZEH balance under different climate conditions. The annual electricity end-use of each building model is compared against each annual on-site PV generation to confirm NZEH performance for both baseline and proposed simulation models. The net-zero energy performance line, shown in Fig. 7, indicates that the ratio of the y-axis to the x-axis needs to be one or greater for NZEH or nearly NZEH performance. This figure shows that all simulation cases under different climates reach good NZEH balances. As expected, the proposed models with the MFVRF-H2R present lower building energy end-use spots compared to the baseline models.

This figure shows that the major contributors to the annual site energy end-use of NZEH baseline models are HVAC and DHW energy consumption. Although heating and cooling energy patterns and their portion for the baseline models can vary significantly depending on weather conditions, the total annual end-uses are similar except for climate 3B. When the MFVRF-H2R is implemented in each model, the total whole-building yearly energy savings are about 5–24% in the selected climate zones. With the MFVRF-H2R, the cooling-dominant climate zones have more total energy savings than the heating-dominant zones. This is because the refrigerant circuit box of the MFVRF-H2R system can control the directions of the refrigerant flow to recover the heat from cooling loads to DHW loads when simultaneous cooling and DHW loads are required during operation hours. The greatest percentage saving for the total annual energy saving is 24% for climate 1A, followed by 17%, 14%, and 12% for climate 2A, 3B, and 3A, respectively. The climate zones under mixed and cool conditions show relatively low savings potential, including 8%, 4%, and 7% for climate 4A, 4C, and 5A, respectively, when the MFVRF-H2R is used as a HVAC alternative.

Figure 9 presents the comparison of cooling and DHW end-use. The results reveal that the proposed models consume about 13–30% less cooling energy use across the climate zones when compared to the baseline models. The most significant cooling site energy savings, approximately 32%, occur in climate 5A, while the smallest savings of around 13% are observed in climate 1A. Conversely, regarding absolute cooling savings, climate 1A demonstrates the highest value, followed by climates 2A, 3B, and other locations. This finding suggests that regions with higher cooling demands offer more opportunities for energy savings. The underlying reason for this trend is a combination of factors. For instance, the potential for heat recovery is comparatively higher during cooling-dominant weather conditions, which can help decrease the load on outdoor operations. However, it is important to note that while greater heat recovery potential is possible when the outdoor air temperature is high, the temperature difference between the inlet and outlet of the DHW system may decrease, leading to reduced DHW energy consumption. This figure also shows the DHW energy savings potential from the baseline models under the climate zones. As expected, the greatest savings for the DHW is about 90% for climate 1A, and the lowest saving is about 16% for climate 4C. Based on such results, it can be concluded that ideal cooling and DHW load balances simultaneously are needed to achieve high energy savings while meeting both cooling and DHW requirements in a residential building.

Figure 10 shows the necessary PV capacity for achieving NZEH performance across various climate zones. As expected, the proposed system demonstrates savings potential in all climate zones, with percentage savings ranging from approximately 4% to 24%. Climate 1A exhibits the most substantial percentage savings in PV capacity, with a 24% reduction when comparing the proposed model with the baseline models. In contrast, climate 4C displays the lowest percentage savings at around 4% compared to the baseline model. These savings are directly correlated to annual site energy end-use. A higher percentage of annual site energy savings allows for a reduction in the number of required PV modules to achieve NZEH performance. Furthermore, locations with hot climates typically experience greater solar irradiance compared to those in mild and cold climates, further enhancing the conditions for attaining zero energy performance. For instance, in climate 1A, five PV modules can be saved while still meeting NZEH performance, primarily due to reduced cooling and DHW usage, as well as increased on-site power generation. Conversely, in climate 5A, the percentage savings for cooling is the highest among the studied climates. However, the DHW savings are comparatively lower than in other locations, leading to the fact that only two PV modules can be saved while maintaining NZEH performance.

A comparative study was conducted to evaluate the effectiveness of the multi-functional VRF system with a domestic hot water loop in achieving net-zero energy performance across various US climate zones. This study employed eQUEST and the post-processing calculation to simulate the NZEH performance and compared the whole-building energy end-use and PV capacity of different designs. The NZEH model was developed based on the design information of the net-zero energy residential test facility constructed by the US NIST, serving as a benchmark for NZEH reference designs. The model’s accuracy was validated using published data from the NIST facility. Upon completion of the validation process, the multi-functional VRF system was incorporated into the NZEH baseline to propose a more energy-efficient NZEH design. The energy end-use and on-site power generation results for both the baseline and the VRF-equipped NZEH models were analyzed under the US climate conditions. The key findings from this study include:

• In cooling-dominant climate zones, the multi-functional VRF system applied to the NZEH models typically yielded greater savings compared to heating-dominant locations. The proposed NZEH model resulted in a 24% annual whole-building end-use savings compared to the baseline model. The cooling and DHW parts, which utilized the refrigerant flow recovery cycle, were significant contributors to the whole-building energy savings achieved by the VRF system.

• The proposed NZEH design demonstrated considerable savings potential for cooling and hot water energy usage. The potential savings for cooling energy end-use were up to about 30%. Furthermore, the multi-functional VRF system applied to the baseline NZEH model resulted in estimated savings of 16–90% for domestic hot water usage. The savings patterns for cooling and DHW, as well as their portions, could vary depending on the amount of recovered heat from the cooling load.

• The study also examined PV capacity savings based on PV generation calculations in eQUEST. By comparing the required PV capacities to achieve NZEH performance as a percentage of savings, the proposed NZEH models featuring the multi-functional VRF system demonstrated lower PV installation requirements compared to the baseline NZEH models, with savings ranging from 7% to 24%, as expected.

The simulated results can be used to evaluate the impact of applying a high energy-efficient heat recovery-enabled VRF system in the design of net-zero residential buildings in different US climate conditions. Future studies could expand the scope of NZEH analysis by utilizing more comprehensive simulation tools, such as EnergyPlus, and optimizing the operation of the proposed approach along with additional renewable and sustainable systems like PV and battery systems in various NZEH designs.

• This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2021R1F1A1064258).

There are no conflicts of interest.

The datasets generated and supporting the findings of this article are obtainable from the corresponding author upon reasonable request.